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We present an online learning algorithm for training structured prediction models with extrinsic loss functions. This allows us to extend a standard supervised learning objective with additional loss-functions, either based on intrinsic or task-specific extrinsic measures of quality. We present experiments with sequence models on part-of-speech tagging and named entity recognition tasks, and with syntactic parsers on dependency parsing and machine translation reordering tasks.
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